1. Technical Field
The present disclosure relates to location of landmark points of interest in volumetric data, and more particularly, to location of landmark points of interest in volumetric data using multi-class classifiers.
2. Discussion of Related Art
Medical imaging is generally recognized as important for diagnosis and patient care. In recent years, medical imaging has experienced an explosive growth due to advances in imaging modalities such as x-rays, computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound. Many existing and emerging imaging modalities are showing great potential for supporting new or improved pre-clinical and clinical applications and workflows. These modalities include MRI, positron emission tomography (PET), single-photon emission computed tomography (SPECT), PET/CT, SPECT/CT, whole-body CT (MDCT), and PET/MR.
A landmark point location system can aid a user in quickly locating a landmark point of interest (e.g., the tip of the lungs) within a medical image comprising one of these imaging modalities. Such a system can result in a more efficient and accurate medical diagnosis.
Conventional landmark point location systems perform a search to exhaustively slide a scanning window over the input image to locate instances of the landmark point of interest. However, such searches are computationally intensive and time consuming.
Thus, there is a need for systems and methods that can more efficiently locate a landmark point of interest in one or more volumes.